The disclosure relates generally to asset management systems, and more particularly, to systems using operational data to manage complex electromechanical assets.
Power generation systems and other complex machines include a large number of mechanical and electrical components, including an increasing number of sensors for detecting operational characteristics and anomalies. These components may be subject to stress and wear, particularly in applications and environments that include motion, pressure, and heat. Managing the operational performance, maintenance, and equipment investments over the life of such a system is challenging and increasingly relies on one or more computing systems for asset management.
Conventional systems and methods exist to monitor the performance and operation of complex machines, sometimes referred to as assets. For example, a power generation system may be equipped with sensors for capturing inputs, outputs, and other operational parameters. Some systems may also be equipped with one or more additional sensors for monitoring specific parameters or components for anomaly detection. The various sensors communicate with one or more processing subsystems, which may, in turn, communicate with one or more computing systems for aggregating sensor data for use in asset management. Asset management systems may employ a variety of computing systems and communication networks to manage the operation, monitoring, and maintenance of one or more assets from which they receive operational and other data.